In a conventional system a traditional imager system typically consists of a single lens and a focal plane array. Recent demand for highly compact thin imaging systems led to broad investigation efforts in sensor design based on focal plane array technologies. A system based on this more recent architecture for reducing the imager thickness can be a system that uses a lenslet array to accumulate a series of sub-images. A specific example of this new architecture is the thin observation module by bound optics (TOMBO) system.
This TOMBO architecture differs from the conventional system because it is a flat architecture that can consist of a lenslet array, a baffle preventing optical cross-talk, and an equivalent focal plane array. If the lenslet array is to be equal to the conventional system lens then n×n number of lenslets can be required to cover the area of the detector, ideally keeping the number of incident photons the same for both configurations. As a result, the depth of optics and sub-image size are n times smaller than the conventional system. The sub-images of the lenslet array can be processed in a manner similar to multi-frame super-resolution to obtain a fully sampled, high-resolution image. The processing task is to reconstruct an image that has resolution as close as possible to the conventional camera lens and the same focal plane array.
The principle of multi-frame super-resolution is that the pixel values from all sub-images are mapped onto an upsampled image plane. Each sub-image position on the super-resolved image plane is determined by its global shift with respect to a reference subimage. In multi-frame super-resolution processing these shifts can be estimated either by iterative procedure or by sub-image registration. The former method is unsuitable for real time applications due to possible convergence problems and heavy computational load, which dramatically increases with respect to the number of sub-images. The accuracy of the latter approach is highly dependent on the nature of the observed scene, such as having some knowledge of the probability density function or noise characteristics of the observed scene.
Accordingly, there remains a need for a method or system that can performs high-resolution image assembly from undersampled sub-images obtained from compact imaging system using lenslet array utilizing scene-independent processing and in a method suitable for real-time applications.